International Journal of Modern Science and Technology

INDEXED IN 

ISSN 2456-0235

​​​​​​​International Journal of Modern Science and Technology, Vol. 2, Special Issue 1, 2017, Pages 60-65.

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​Efficient Design of Grid Connected Wind Energy Conversion System using PMSG

R. Varmela, S. Chandrasekaran
Department of Electrical and Electronics Engineering, Arasu Engineering College, Kumbakonam – 612 501. India.

​*Corresponding author’s e-mail: varmela@gmail.com

​Abstract
This paper deals with permanent magnet synchronous generator (PMSG) based wind energy conversion system (WECS) integrated with grid with two back to back connected converters with a common DC link. The aim of this research is to model control of direct driven 1.5 MW wind turbine permanent magnetic synchronous generator (PMSG) which feeds alternating current (AC) power to the utility grid .The machine side converter is used to extract maximum power from the wind. In this paper a study of WECS is done by using a constant speed direct-driven wind turbine in Matlab. Moreover, by maintaining the dc link voltage at its reference value, the output ac voltage of the inverter can be kept constant irrespective of variations in the wind speed and load. An effective control techniques to extract maximum power from wind turbine is maximum power point tracking controller (MPPT), grid  side controller also called voltage controller, pitch controller, phase lock loop controller (PLL) also used in this project, transformer used for isolation purpose, crow bar circuit used for protection the whole system.

​​Keywords: Permanent Magnet Synchronous Generator; Wind Energy Conversion; Phase Locked Loop Controller; Maximum Power Point tracking; Designing of wind energy system.

​References

  1. de Castro Souza GB, Vieira FHT, Lima C R, Júnior GAD, Castro MS, Araujo SG, Vasques TL. Developing Smart Grids Based on GPRS and ZigBee Technologies Using Queuing Modeling-Based Optimization Algorithm. ETRI Journal. 2016;38:41–51.
  2. Deng R, Yang Z, Chow MY, Chen J. A Survey on Demand Response in Smart Grids: Mathematical Models and Approaches. IEEE Trans Ind Informatics. 2015;11(3):570–582.
  3. Park Y, Kim S. Bargaining-Based Smart Grid Pricing Model for Demand Side Management Scheduling. ETRI Journal. 2015;37:197–202.
  4. Golestan S, Monfared M, Freijedo FD, Guerrero JM. Performance Improvement of a Prefiltered Synchronous-Reference Frame PLL by Using a PID-Type Loop Filter. IEEE Trans Ind Electron. 2014;61:3469-3479.
  5. Shoeiby B, Davoodnezhad R, Holmes DG, McGrath BP. Voltage-frequency control of an islanded microgrid using the intrinsic droop characteristics of resonant current regulators. IEEE Energy Conversion Congress and Exposition, Pittsburgh, PA, 2014. pp. 68-75.  
  6. Krause PC, Wasynczuk O, Sudhof S, Pekarak S. Analysis of Electric Machinery and Drive Systems (3rd ed.). Wiley-IEEE Press, New Jersey, 2013.
  7. Lin CH. Recurrent modified Elman neural network control of PM synchronous generator system using wind turbine emulator of PM synchronous servo motor drive. International Journal of Electrical Power and Energy Systems. 2013;52:143-160.
  8. Gungor VC, Sahin D, Kocak T, Ergut S, Buccella C, Cecati C, Hancke GP. A Survey on smart grid potential applications and communication     requirements. IEEE Trans Ind Informatics. 2013;9:28–42.
  9. Kumar Nunna H. S. V. S, Doolla S. Multiagent based distributedenergy resource management for intelligent microgrids. IEEE Tran Ind Electron. 2013;60:1678–1687.
  10. Robert G, Jochen T. Wind Power Plants: Fundamentals, Design, Construction and Operation, Springer 2012.